Reconnaissance, surveillance and target acquisition systems can include a plurality of airborne platforms or air vehicles, each carrying a plurality of sensors that are used to collect information about an area and/or target of interest. The airborne platforms can communicate with requesters, which can include persons or equipment that desire access to data collected by the sensors. This network centric environment is critical to share awareness, enhance collaboration among various forces, and expand understanding of the battlefield conditions.
In some instances, a plurality of sensors can be used to collect information about an area and/or target of interest. The information produced by these sensors can be combined to enhance the accuracy of decisions or estimates based on the information. Conflicting decisions made by multiple sensors on the same platform or within the network may confuse the participants.
Industry standards for decision level fusion such as Dempster-Shafer have limited optimization space potentially yielding unreliable fused decisions. Other decision level fusion systems use heuristic rules that are application specific and are not easily generalized.
There is a critical need for a decision level fusion process that maximizes the synergy among decision sources to reduce target ambiguity, produce timely and accurate decisions, and reduce fratricide and operator workload.